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Optimization Issues in KL-Constrained Approximate Policy Iteration

Feb 11, 2021
Nevena Lazić, Botao Hao, Yasin Abbasi-Yadkori, Dale Schuurmans, Csaba Szepesvári


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Bootstrapping Statistical Inference for Off-Policy Evaluation

Feb 09, 2021
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang


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On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function

Feb 04, 2021
Gellert Weisz, Philip Amortila, Barnabás Janzer, Yasin Abbasi-Yadkori, Nan Jiang, Csaba Szepesvári


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Asymptotically Optimal Information-Directed Sampling

Nov 11, 2020
Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvári


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Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient

Nov 08, 2020
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang


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Online Sparse Reinforcement Learning

Nov 08, 2020
Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang


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On Optimality of Meta-Learning in Fixed-Design Regression with Weighted Biased Regularization

Oct 31, 2020
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári


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Online Algorithm for Unsupervised Sequential Selection with Contextual Information

Oct 23, 2020
Arun Verma, Manjesh K. Hanawal, Csaba Szepesvári, Venkatesh Saligrama

* Accepted to NeurIPS 2020 

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CoinDICE: Off-Policy Confidence Interval Estimation

Oct 22, 2020
Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans

* To appear at NeurIPS 2020 as spotlight 

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Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions

Oct 03, 2020
Gellert Weisz, Philip Amortila, Csaba Szepesvári


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Tighter risk certificates for neural networks

Aug 12, 2020
María Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári

* Preprint under review 

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Efficient Planning in Large MDPs with Weak Linear Function Approximation

Jul 13, 2020
Roshan Shariff, Csaba Szepesvári

* 12 pages and appendix (10 pages). Submitted to the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada 

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Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting

Jun 18, 2020
Ilja Kuzborskij, Claire Vernade, András György, Csaba Szepesvári


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Efron-Stein PAC-Bayesian Inequalities

Sep 04, 2019
Ilja Kuzborskij, Csaba Szepesvári


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Detecting Overfitting via Adversarial Examples

Mar 06, 2019
Roman Werpachowski, András György, Csaba Szepesvári

* 25 pages 

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Distribution-Dependent Analysis of Gibbs-ERM Principle

Feb 05, 2019
Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári


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Online Algorithm for Unsupervised Sensor Selection

Jan 15, 2019
Arun Verma, Manjesh K. Hanawal, Csaba Szepesvári, Venkatesh Saligrama

* Accepted at AIStats 2019 

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LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration

Jul 02, 2018
Gellért Weisz, András György, Csaba Szepesvári

* to appear at ICML 2018 

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Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging

Sep 12, 2017
Chandrashekar Lakshminarayanan, Csaba Szepesvári

* 16 pages, 2 figures, was submitted to NIPS 2017 

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A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds

Sep 08, 2017
Pooria Joulani, András György, Csaba Szepesvári

* Accepted to The 28th International Conference on Algorithmic Learning Theory (ALT 2017). 40 pages 

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Mixing time estimation in reversible Markov chains from a single sample path

Aug 24, 2017
Daniel Hsu, Aryeh Kontorovich, David A. Levin, Yuval Peres, Csaba Szepesvári

* 34 pages, merges results of arXiv:1506.02903 and arXiv:1612.05330 

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Structured Best Arm Identification with Fixed Confidence

Jun 19, 2017
Ruitong Huang, Mohammad M. Ajallooeian, Csaba Szepesvári, Martin Müller


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Bernoulli Rank-$1$ Bandits for Click Feedback

Mar 19, 2017
Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen


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SDP Relaxation with Randomized Rounding for Energy Disaggregation

Oct 29, 2016
Kiarash Shaloudegi, András György, Csaba Szepesvári, Wilsun Xu


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(Bandit) Convex Optimization with Biased Noisy Gradient Oracles

Sep 22, 2016
Xiaowei Hu, Prashanth L. A., András György, Csaba Szepesvári


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Multiclass Classification Calibration Functions

Sep 20, 2016
Bernardo Ávila Pires, Csaba Szepesvári

* 44 pages 

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Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models

Sep 20, 2016
Bernardo Ávila Pires, Csaba Szepesvári

* JMLR W&CP 49: COLT 2016 Proceedings (2016) 1-31 
* 30 pages. Corrected typos. Appears in JMLR Workshop and Conference Proceedings 49: Proceedings of the 29th Annual Conference on Learning Theory (COLT 2016) 

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Chaining Bounds for Empirical Risk Minimization

Sep 07, 2016
Gábor Balázs, András György, Csaba Szepesvári


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